カオス挙動と分数階メモリを伴う炭素クレジット投資システムの動的解析と制御
Dynamical Analysis and Control of a Carbon Credit Investment System with Chaotic Behavior and Fractional-Order Memory (原題)
Sofia E. Krzyuy, Giane Gonçalves Lenzi, Maria E. K. Fuziki, José Manoel Balthazar, Leda Maria Saragiotto Colpini, Onélia Aparecida Andreo dos Santos, Ângelo Marcelo Tusset
🤖 gxceed AI 要約
日本語
本研究は、非線形解析、分数階モデリング、能動制御技術を用いて炭素クレジット投資システムの動的挙動を調査する。グリーン投資需要と炭素税率のパラメータに焦点を当て、分岐図、位相ポートレート、リアプノフ指数を用いて周期・カオス挙動を特定。分数階微分の次数がシステム動態に影響を与えることを示し、LQRとSDREコントローラによりカオスを抑制し平衡状態へ導く。状態観測器を用いて未測定変数を推定する。
English
This study investigates the dynamic behavior of a carbon credit investment system using nonlinear analysis, fractional-order modeling, and active control. It identifies periodic and chaotic regimes via bifurcation diagrams and Lyapunov exponents, showing that fractional derivative order significantly affects dynamics. LQR and SDRE controllers successfully stabilize the system to desired equilibria with low tracking errors, and state observers estimate unmeasured variables. Findings provide quantitative insights into carbon credit investment dynamics and control applicability.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のカーボンクレジット市場（J-クレジット）や排出量取引制度の設計において、炭素税率や投資需要の変動が市場の安定性に与える影響を理解するための理論的枠組みを提供する。ただし、実証データや具体的な政策提言は含まれておらず、実務への直接的な示唆は限定的。
In the global GX context
This paper contributes to the global discourse on carbon pricing and market stability by modeling carbon credit investment dynamics with fractional-order memory. It offers a theoretical basis for understanding how carbon tax rates and green investment demand can lead to chaotic behavior, which is relevant for designing robust carbon markets under the Paris Agreement and Article 6 mechanisms. However, the lack of empirical validation limits its direct applicability to policy design.
👥 読者別の含意
🔬研究者:Provides a mathematical framework for analyzing carbon credit market dynamics, useful for further research on market stability and control.
🏛政策担当者:Offers theoretical insights into how carbon tax rates and investment demand can affect market stability, potentially informing market design.
📄 Abstract（原文）
This study investigates the dynamic behavior of a carbon credit investment system using nonlinear analysis, fractional-order modeling, and active control techniques. The analysis focuses on parameters associated with the demand for green investments and the impact of the carbon tax rate. System dynamics are characterized through bifurcation diagrams, phase portraits, time series, and Lyapunov exponents, enabling the identification of distinct dynamic regimes, including periodic and chaotic behaviors. To incorporate memory effects inherent in economic variables, fractional-order formulations based on the Riemann–Liouville operator are employed, revealing that the order of the fractional derivative significantly influences the system's dynamics. To stabilize the system and suppress chaotic behavior, a linear controller of the Linear Quadratic Regulator (LQR) type and a nonlinear controller based on the State-Dependent Riccati Equation (SDRE) are designed. The results demonstrate that both strategies successfully drive the system toward desired equilibrium states while exhibiting low tracking errors. Furthermore, addressing scenarios where not all state variables are directly available for feedback, state observers are utilized to estimate unmeasured variables and supply the necessary information to the controllers. The findings provide a quantitative basis for understanding the complex dynamics associated with carbon credit investments and highlight the applicability of control strategies for system stabilization and the mitigation of undesirable dynamic behaviors.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.65582/gd.2026.010first seen 2026-08-29 04:43:13
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